Wrangle SPINS gradients with GSR

Grabbing SPINS gradients

library(tidyverse)

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Read in the SPINS big table

spins_grads <- read_csv("../gsr_spins_concat_full")

## Warning: Missing column names filled in: 'X1' [1]

## 
## ── Column specification ────────────────────────────────────────────────────────
## cols(
##   X1 = col_double(),
##   grad1 = col_double(),
##   grad2 = col_double(),
##   grad3 = col_double(),
##   grad4 = col_double(),
##   grad5 = col_double(),
##   grad6 = col_double(),
##   grad7 = col_double(),
##   grad8 = col_double(),
##   grad9 = col_double(),
##   grad10 = col_double(),
##   ROI = col_character(),
##   Task = col_character(),
##   Subject = col_character(),
##   Network = col_character(),
##   Site = col_character()
## )

# spins_grads <- spins_grads %>%
#   mutate(site = str_sub(`Subject`, 5, 7)) %>%
#   rename(task = `EA or RS`, 
#          subject = `Subject ID`)

read subject data

lol_spins_behav <- 
  read_csv('../data/spins_lolivers_subject_info_for_grads_2021-07-29.csv')

## 
## ── Column specification ────────────────────────────────────────────────────────
## cols(
##   .default = col_logical(),
##   record_id = col_character(),
##   site = col_character(),
##   scanner = col_character(),
##   diagnostic_group = col_character(),
##   demo_sex = col_character(),
##   demo_age_study_entry = col_double(),
##   `fd_mean.emp_run-1_bold` = col_double(),
##   `fd_mean.emp_run-2_bold` = col_double(),
##   `fd_mean.emp_run-3_bold` = col_double(),
##   fd_mean.rest_bold = col_double(),
##   fd_max_emp = col_double(),
##   fd_mean_emp = col_double(),
##   subject = col_character()
## )
## ℹ Use `spec()` for the full column specifications.

grab some network colours

networks <- read_delim("../networks.txt", 
    "\t", escape_double = FALSE, trim_ws = TRUE) %>%
  select(NETWORK, NETWORKKEY, RED, GREEN, BLUE, ALPHA) %>%
  distinct() %>%
  add_row(NETWORK = "Subcortical", NETWORKKEY = 13, RED = 0, GREEN=0, BLUE=0, ALPHA=255) %>%
  mutate(hex = rgb(RED, GREEN, BLUE, maxColorValue = 255)) %>%
  arrange(NETWORKKEY)

## 
## ── Column specification ────────────────────────────────────────────────────────
## cols(
##   INDEX = col_double(),
##   KEYVALUE = col_double(),
##   LABEL = col_character(),
##   RED = col_double(),
##   GREEN = col_double(),
##   BLUE = col_double(),
##   ALPHA = col_double(),
##   HEMISPHERE = col_character(),
##   NETWORK = col_character(),
##   NETWORKKEY = col_double(),
##   NETWORKSORTEDORDER = col_double(),
##   GLASSERLABELNAME = col_character()
## )

networks

fitting models

Models

• model includes DX, sex, age, scanner, fd?

• what about between task -

  • do paired ttest?

So the current df is here: /projects/loliver/SPINS_PLS_Conn/data/processed/spins_behav_ea_conn_04-29-2021.csv 6:27 However, I also excluded ZHP_0110 and ZHP_0172 as they did not complete the soc cog tasks 6:27 So that df includes 356, but my current N is 354

The following participants were missing task-rest cleaned files: sub-CMP0180 sub-CMP0182 sub-CMP0191 sub-CMP0196 sub-CMP0198 sub-CMP0207 sub-CMP0213 sub-ZHH0034

The following participants were missing task-emp background files: sub-CMH0025 sub-CMH0044 sub-CMH0095 sub-CMH0138 sub-MRC0075 sub-MRP0077 sub-MRP0147 sub-MRP0149 sub-MRP0151 sub-MRP0161 sub-ZHH0038 sub-ZHP0061 sub-ZHP0086

grand_mean_grads <- spins_grads %>%
  mutate(Network = factor(Network, levels = networks$NETWORK)) %>%
  filter(Subject %in% lol_spins_behav$subject) %>%
  group_by(Site, Task, ROI, Network) %>%
  summarise_at(vars(starts_with("grad")), mean)

grand_mean_grads

grand_mean_grads %>%
  ggplot(aes(x = grad1, y = grad2, colour = Network)) +
  geom_point() +
  scale_color_manual(values = networks$hex) +
  facet_grid(Task ~ Site)

grand_mean_grads %>%
  ggplot(aes(x = grad1, y = grad3, colour = Network)) +
  geom_point() +
  scale_color_manual(values = networks$hex) +
  facet_grid(Task ~ Site)

grand_mean_grads %>%
  ggplot(aes(x = grad2, y = grad3, colour = Network)) +
  geom_point() +
  scale_color_manual(values = networks$hex) +
  facet_grid(Task ~ Site)

grand_mean_grads %>%
  ggplot(aes(x = grad1, y = grad4, colour = Network)) +
  geom_point() +
  scale_color_manual(values = networks$hex) +
  facet_grid(Task ~ Site)

From age paper: Each axis of this 3D space was defined by the values along the first three gradients. Within network dispersion was quantified as sum squared Euclidean distance of network nodes to the network centroid at individual level. Between network dispersion was calculated as the Euclidean distance between network centroids.

They also did linear models on nodal values from the first three gradients

calculating centroid and within network dispersion

## calculate the network centers
subject_level_centers <- spins_grads %>%
  filter(Subject %in% lol_spins_behav$subject) %>%
  group_by(Site, Task, Network, Subject) %>%
  summarise_at(c("grad1", "grad2", "grad3"), mean)
  
subject_within_dispersion <- subject_level_centers %>%
  
  ## combine with orig spins grads
  inner_join(spins_grads, by = c("Site", "Task", "Network", "Subject"), suffix = c("_center", "")) %>%
  
  ## calculate squared euclidian distance from the network centroid  
  ungroup() %>%
  mutate(roi_distance_sq = (grad1_center - grad1)**2 + (grad2_center - grad2)**2 + (grad3_center - grad3)**2) %>% 
  
  ## dispersion as the sum of the squared distances within network and participant
  group_by(Site, Task, Network, Subject) %>%
  summarise(within_dispersion = sum(roi_distance_sq))

## `summarise()` has grouped output by 'Site', 'Task', 'Network'. You can override using the `.groups` argument.

calculating between network dispersion

Between network dispersion was calculated as the Euclidean distance between network centroids.

library(igraph)

## 
## Attaching package: 'igraph'

## The following objects are masked from 'package:dplyr':
## 
##     as_data_frame, groups, union

## The following objects are masked from 'package:purrr':
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## The following object is masked from 'package:tidyr':
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##     as_data_frame

## The following objects are masked from 'package:stats':
## 
##     decompose, spectrum

## The following object is masked from 'package:base':
## 
##     union

## assumes that the network_centroids contains columns "Network", "grad1", "grad2", "grad3"
calc_between_distances <- function(network_centoids) {
  ## grab the unique network node names
  network_names <- unique(network_centoids$Network)

  ## create a graph dataframe of edges
  result <- make_full_graph(length(network_names), directed = FALSE) %>% as_data_frame()
  
  for (i in 1:nrow(result)) {
    to_name <- network_names[result$to[i]]
    from_name <- network_names[result$from[i]]
   
    result$to_name[i] <- to_name
    result$from_name[i] <- from_name

  res_df <- test_centroids %>%
    filter(Network == to_name | Network == from_name) %>%
    mutate_at(vars(c("grad1", "grad2", "grad3")), function(x) {(x - lag(x))**2}) %>%
    mutate(eucl_dist = sqrt(grad1 + grad2 + grad3))

  result$eucl_dist[i] <- res_df$eucl_dist[2]

  }

  return(result %>% select(to_name, from_name, eucl_dist))
}

between_network <- subject_level_centers %>%
  ungroup() %>%
  group_by(Site, Task, Subject) %>%
  nest() %>%
  mutate(distances = map(data, calc_between_distances)) 

library(broom)
subject_level_centers %>%
  inner_join(lol_spins_behav, by = c("Subject" = "subject")) %>%
  mutate( fd_mean = if_else(Task=="EA", fd_mean_emp, `fd_mean.rest_bold`)) %>%
  ungroup() %>%
  group_by(Network) %>%
  do(tidy(aov(grad1 ~ Task + fd_mean_emp + scanner + Error(Subject), data = .))) %>%
  knitr::kable()

Network	stratum	term	df	sumsq	meansq	statistic	p.value
Auditory	Subject	fd_mean_emp	1	0.3641676	0.3641676	22.0720637	0.0000038
Auditory	Subject	scanner	5	0.8568149	0.1713630	10.3862459	0.0000000
Auditory	Subject	Residuals	340	5.6096700	0.0164990	NA	NA
Auditory	Within	Task	1	2.1693074	2.1693074	172.0018255	0.0000000
Auditory	Within	Residuals	346	4.3637929	0.0126121	NA	NA
Cingulo-Opercular	Subject	fd_mean_emp	1	0.3349874	0.3349874	44.4056434	0.0000000
Cingulo-Opercular	Subject	scanner	5	0.2603116	0.0520623	6.9013348	0.0000037
Cingulo-Opercular	Subject	Residuals	340	2.5648932	0.0075438	NA	NA
Cingulo-Opercular	Within	Task	1	0.4599271	0.4599271	82.8383865	0.0000000
Cingulo-Opercular	Within	Residuals	346	1.9210269	0.0055521	NA	NA
Default	Subject	fd_mean_emp	1	0.4716523	0.4716523	40.7667179	0.0000000
Default	Subject	scanner	5	0.2417948	0.0483590	4.1798504	0.0010644
Default	Subject	Residuals	340	3.9336449	0.0115695	NA	NA
Default	Within	Task	1	2.3251745	2.3251745	300.0467949	0.0000000
Default	Within	Residuals	346	2.6812830	0.0077494	NA	NA
Dorsal-Attention	Subject	fd_mean_emp	1	0.0214715	0.0214715	2.9369777	0.0874840
Dorsal-Attention	Subject	scanner	5	0.1322006	0.0264401	3.6166032	0.0033528
Dorsal-Attention	Subject	Residuals	340	2.4856594	0.0073108	NA	NA
Dorsal-Attention	Within	Task	1	0.0514999	0.0514999	9.1518003	0.0026706
Dorsal-Attention	Within	Residuals	346	1.9470454	0.0056273	NA	NA
Frontoparietal	Subject	fd_mean_emp	1	0.3005887	0.3005887	31.9516804	0.0000000
Frontoparietal	Subject	scanner	5	0.3664047	0.0732809	7.7895454	0.0000006
Frontoparietal	Subject	Residuals	340	3.1985847	0.0094076	NA	NA
Frontoparietal	Within	Task	1	1.7578251	1.7578251	266.3016782	0.0000000
Frontoparietal	Within	Residuals	346	2.2839041	0.0066009	NA	NA
Language	Subject	fd_mean_emp	1	0.1480215	0.1480215	10.6038041	0.0012422
Language	Subject	scanner	5	0.2588106	0.0517621	3.7080795	0.0027858
Language	Subject	Residuals	340	4.7461547	0.0139593	NA	NA
Language	Within	Task	1	0.1373327	0.1373327	13.1559501	0.0003297
Language	Within	Residuals	346	3.6118352	0.0104388	NA	NA
Orbito-Affective	Subject	fd_mean_emp	1	0.0011489	0.0011489	0.0767487	0.7819212
Orbito-Affective	Subject	scanner	5	0.0747757	0.0149551	0.9990240	0.4182529
Orbito-Affective	Subject	Residuals	340	5.0897161	0.0149698	NA	NA
Orbito-Affective	Within	Task	1	0.2858827	0.2858827	26.0053259	0.0000006
Orbito-Affective	Within	Residuals	346	3.8036601	0.0109932	NA	NA
Posterior-Multimodal	Subject	fd_mean_emp	1	0.0000198	0.0000198	0.0007252	0.9785324
Posterior-Multimodal	Subject	scanner	5	0.0842328	0.0168466	0.6183091	0.6859403
Posterior-Multimodal	Subject	Residuals	340	9.2636979	0.0272462	NA	NA
Posterior-Multimodal	Within	Task	1	0.3942566	0.3942566	31.0817744	0.0000000
Posterior-Multimodal	Within	Residuals	346	4.3888353	0.0126845	NA	NA
Somatomotor	Subject	fd_mean_emp	1	0.4423978	0.4423978	34.5354962	0.0000000
Somatomotor	Subject	scanner	5	0.2050523	0.0410105	3.2014540	0.0077211
Somatomotor	Subject	Residuals	340	4.3553814	0.0128099	NA	NA
Somatomotor	Within	Task	1	2.0056268	2.0056268	220.4347105	0.0000000
Somatomotor	Within	Residuals	346	3.1480836	0.0090985	NA	NA
Subcortical	Subject	fd_mean_emp	1	0.0731462	0.0731462	10.2574148	0.0014900
Subcortical	Subject	scanner	5	0.0182739	0.0036548	0.5125148	0.7667966
Subcortical	Subject	Residuals	340	2.4245596	0.0071311	NA	NA
Subcortical	Within	Task	1	0.0374143	0.0374143	6.1877745	0.0133340
Subcortical	Within	Residuals	346	2.0920866	0.0060465	NA	NA
Ventral-Multimodal	Subject	fd_mean_emp	1	0.0000435	0.0000435	0.0021813	0.9627762
Ventral-Multimodal	Subject	scanner	5	0.1395341	0.0279068	1.4009119	0.2233415
Ventral-Multimodal	Subject	Residuals	340	6.7729600	0.0199205	NA	NA
Ventral-Multimodal	Within	Task	1	0.2317625	0.2317625	11.3864411	0.0008237
Ventral-Multimodal	Within	Residuals	346	7.0425719	0.0203543	NA	NA
Visual1	Subject	fd_mean_emp	1	0.0894716	0.0894716	3.7360894	0.0540791
Visual1	Subject	scanner	5	0.2763372	0.0552674	2.3078180	0.0440452
Visual1	Subject	Residuals	340	8.1422931	0.0239479	NA	NA
Visual1	Within	Task	1	0.0392833	0.0392833	1.8594923	0.1735699
Visual1	Within	Residuals	346	7.3095276	0.0211258	NA	NA
Visual2	Subject	fd_mean_emp	1	0.1624415	0.1624415	19.6307351	0.0000127
Visual2	Subject	scanner	5	0.2908200	0.0581640	7.0290036	0.0000029
Visual2	Subject	Residuals	340	2.8134516	0.0082749	NA	NA
Visual2	Within	Task	1	1.5586961	1.5586961	198.8719691	0.0000000
Visual2	Within	Residuals	346	2.7118394	0.0078377	NA	NA

results_subject_within_dispersion <- subject_within_dispersion %>%
  inner_join(lol_spins_behav, by = c("Subject" = "subject")) %>%
  mutate( fd_mean = if_else(Task=="EA", fd_mean_emp, `fd_mean.rest_bold`)) %>%
  group_by(Network, Task) %>%
  do(tidy(lm(within_dispersion ~ diagnostic_group + demo_age_study_entry + demo_sex + fd_mean + scanner, data = .))) %>%
  ungroup() %>%
  group_by(term) %>%
  mutate(p_FDR = p.adjust(p.value, method = "fdr"))

results_subject_within_dispersion %>%
  filter(term == "diagnostic_groupcontrol") %>%
  knitr::kable()

Network	Task	term	estimate	std.error	statistic	p.value	p_FDR
Auditory	EA	diagnostic_groupcontrol	-0.0221795	0.0309387	-0.7168855	0.4739413	0.6888323
Auditory	RS	diagnostic_groupcontrol	0.0999724	0.0683704	1.4622176	0.1446135	0.4699938
Cingulo-Opercular	EA	diagnostic_groupcontrol	0.0992081	0.2140203	0.4635454	0.6432727	0.8362545
Cingulo-Opercular	RS	diagnostic_groupcontrol	0.3931632	0.3239122	1.2137957	0.2256757	0.5192920
Default	EA	diagnostic_groupcontrol	-0.6929686	0.2628557	-2.6363079	0.0087692	0.0901199
Default	RS	diagnostic_groupcontrol	0.3864732	0.4827888	0.8005017	0.4239841	0.6888323
Dorsal-Attention	EA	diagnostic_groupcontrol	-0.0428020	0.1156782	-0.3700094	0.7116079	0.8409912
Dorsal-Attention	RS	diagnostic_groupcontrol	0.4549504	0.1708437	2.6629621	0.0081173	0.0901199
Frontoparietal	EA	diagnostic_groupcontrol	-0.5036294	0.1969466	-2.5571875	0.0109897	0.0901199
Frontoparietal	RS	diagnostic_groupcontrol	-0.7514029	0.3037572	-2.4736959	0.0138646	0.0901199
Language	EA	diagnostic_groupcontrol	-0.2127577	0.0990738	-2.1474678	0.0324689	0.1406986
Language	RS	diagnostic_groupcontrol	-0.1733343	0.1713951	-1.0113139	0.3125918	0.5805276
Orbito-Affective	EA	diagnostic_groupcontrol	-0.0045974	0.0121072	-0.3797240	0.7043895	0.8409912
Orbito-Affective	RS	diagnostic_groupcontrol	-0.0415057	0.0353485	-1.1741840	0.2411504	0.5192920
Posterior-Multimodal	EA	diagnostic_groupcontrol	-0.0249051	0.0349732	-0.7121189	0.4768839	0.6888323
Posterior-Multimodal	RS	diagnostic_groupcontrol	0.0035891	0.0666705	0.0538337	0.9570996	0.9570996
Somatomotor	EA	diagnostic_groupcontrol	-0.0488648	0.1041735	-0.4690711	0.6393221	0.8362545
Somatomotor	RS	diagnostic_groupcontrol	0.4158732	0.2185773	1.9026363	0.0579402	0.2152063
Subcortical	EA	diagnostic_groupcontrol	0.1069146	0.0946875	1.1291303	0.2596460	0.5192920
Subcortical	RS	diagnostic_groupcontrol	0.4563074	0.1929949	2.3643499	0.0186282	0.0968668
Ventral-Multimodal	EA	diagnostic_groupcontrol	-0.0006241	0.0051602	-0.1209375	0.9038126	0.9570996
Ventral-Multimodal	RS	diagnostic_groupcontrol	-0.0316949	0.0235153	-1.3478422	0.1786145	0.5159974
Visual1	EA	diagnostic_groupcontrol	-0.0015026	0.0268451	-0.0559744	0.9553954	0.9570996
Visual1	RS	diagnostic_groupcontrol	-0.0680618	0.0551739	-1.2335871	0.2182165	0.5192920
Visual2	EA	diagnostic_groupcontrol	0.0569670	0.1760929	0.3235053	0.7465132	0.8438845
Visual2	RS	diagnostic_groupcontrol	0.2712569	0.3767612	0.7199704	0.4720422	0.6888323

results_subject_within_dispersion %>%
  filter(term == "demo_age_study_entry") %>%
  knitr::kable()

Network	Task	term	estimate	std.error	statistic	p.value	p_FDR
Auditory	EA	demo_age_study_entry	-0.0000988	0.0016345	-0.0604371	0.9518433	0.9518433
Auditory	RS	demo_age_study_entry	0.0005796	0.0037155	0.1559859	0.8761375	0.9491490
Cingulo-Opercular	EA	demo_age_study_entry	-0.0472094	0.0113071	-4.1752069	0.0000379	0.0004933
Cingulo-Opercular	RS	demo_age_study_entry	-0.0126022	0.0176027	-0.7159244	0.4745338	0.8225253
Default	EA	demo_age_study_entry	-0.0416489	0.0138871	-2.9991011	0.0029092	0.0189100
Default	RS	demo_age_study_entry	-0.0092580	0.0262367	-0.3528639	0.7244111	0.8968899
Dorsal-Attention	EA	demo_age_study_entry	-0.0193355	0.0061115	-3.1637989	0.0016990	0.0147247
Dorsal-Attention	RS	demo_age_study_entry	0.0120384	0.0092843	1.2966338	0.1956444	0.4235606
Frontoparietal	EA	demo_age_study_entry	-0.0449890	0.0104050	-4.3237692	0.0000202	0.0004933
Frontoparietal	RS	demo_age_study_entry	-0.0214694	0.0165074	-1.3005949	0.1942858	0.4235606
Language	EA	demo_age_study_entry	-0.0065484	0.0052342	-1.2510602	0.2117803	0.4235606
Language	RS	demo_age_study_entry	-0.0044197	0.0093143	-0.4745060	0.6354465	0.8968899
Orbito-Affective	EA	demo_age_study_entry	-0.0008387	0.0006396	-1.3111766	0.1906908	0.4235606
Orbito-Affective	RS	demo_age_study_entry	0.0030955	0.0019210	1.6114026	0.1080281	0.3510914
Posterior-Multimodal	EA	demo_age_study_entry	-0.0044179	0.0018477	-2.3910073	0.0173505	0.0902224
Posterior-Multimodal	RS	demo_age_study_entry	0.0015324	0.0036231	0.4229378	0.6726104	0.8968899
Somatomotor	EA	demo_age_study_entry	0.0102813	0.0055037	1.8680730	0.0626195	0.2325868
Somatomotor	RS	demo_age_study_entry	0.0021319	0.0118784	0.1794818	0.8576673	0.9491490
Subcortical	EA	demo_age_study_entry	-0.0115726	0.0050025	-2.3133664	0.0213040	0.0923172
Subcortical	RS	demo_age_study_entry	-0.0142556	0.0104881	-1.3592121	0.1749883	0.4235606
Ventral-Multimodal	EA	demo_age_study_entry	-0.0002191	0.0002726	-0.8038591	0.4220450	0.7837979
Ventral-Multimodal	RS	demo_age_study_entry	0.0005797	0.0012779	0.4536643	0.6503625	0.8968899
Visual1	EA	demo_age_study_entry	-0.0001441	0.0014183	-0.1016220	0.9191172	0.9518433
Visual1	RS	demo_age_study_entry	-0.0008586	0.0029984	-0.2863701	0.7747706	0.9156380
Visual2	EA	demo_age_study_entry	-0.0044399	0.0093033	-0.4772387	0.6335015	0.8968899
Visual2	RS	demo_age_study_entry	0.0076648	0.0204747	0.3743528	0.7083773	0.8968899

net_centroids_results <- subject_level_centers %>%
  inner_join(lol_spins_behav, by = c("Subject" = "subject")) %>%
  mutate( fd_mean = if_else(Task=="EA", fd_mean_emp, `fd_mean.rest_bold`)) %>%

  pivot_longer(starts_with("grad"), names_to = "grad_num", values_to = "grad_value") %>%
    ungroup() %>%
  group_by(Network, Task, grad_num) %>%
  do(tidy(lm(grad_value ~ diagnostic_group + demo_age_study_entry + demo_sex + fd_mean + scanner, data = .))) %>%
  ungroup() %>%
  group_by(term) %>%
  mutate(p_FDR = p.adjust(p.value, method = "fdr"))

net_centroids_results %>%
  filter(term == "diagnostic_groupcontrol") %>%
  arrange(grad_num, Task) %>%
  knitr::kable()

Network	Task	grad_num	term	estimate	std.error	statistic	p.value	p_FDR
Auditory	EA	grad1	diagnostic_groupcontrol	0.0239680	0.0092808	2.5825409	0.0102288	0.0379928
Cingulo-Opercular	EA	grad1	diagnostic_groupcontrol	0.0146874	0.0068312	2.1500320	0.0322639	0.1006633
Default	EA	grad1	diagnostic_groupcontrol	-0.0376677	0.0078740	-4.7838048	0.0000026	0.0001005
Dorsal-Attention	EA	grad1	diagnostic_groupcontrol	0.0065356	0.0061926	1.0553855	0.2920051	0.5066699
Frontoparietal	EA	grad1	diagnostic_groupcontrol	-0.0083782	0.0065259	-1.2838482	0.2000771	0.3901503
Language	EA	grad1	diagnostic_groupcontrol	0.0145716	0.0079548	1.8317936	0.0678647	0.1764481
Orbito-Affective	EA	grad1	diagnostic_groupcontrol	0.0004807	0.0087882	0.0547014	0.9564087	0.9564087
Posterior-Multimodal	EA	grad1	diagnostic_groupcontrol	-0.0064001	0.0108629	-0.5891675	0.5561436	0.6730968
Somatomotor	EA	grad1	diagnostic_groupcontrol	0.0162528	0.0089713	1.8116381	0.0709322	0.1784746
Subcortical	EA	grad1	diagnostic_groupcontrol	-0.0014148	0.0052628	-0.2688300	0.7882250	0.8513553
Ventral-Multimodal	EA	grad1	diagnostic_groupcontrol	-0.0095459	0.0100210	-0.9525960	0.3414775	0.5790271
Visual1	EA	grad1	diagnostic_groupcontrol	0.0068381	0.0091587	0.7466176	0.4558150	0.6348852
Visual2	EA	grad1	diagnostic_groupcontrol	0.0168989	0.0061751	2.7366396	0.0065361	0.0299890
Auditory	RS	grad1	diagnostic_groupcontrol	0.0336612	0.0161283	2.0870909	0.0376309	0.1128928
Cingulo-Opercular	RS	grad1	diagnostic_groupcontrol	0.0357243	0.0097576	3.6611913	0.0002914	0.0036180
Default	RS	grad1	diagnostic_groupcontrol	-0.0345143	0.0122000	-2.8290313	0.0049485	0.0257323
Dorsal-Attention	RS	grad1	diagnostic_groupcontrol	-0.0016279	0.0107539	-0.1513808	0.8797659	0.9029177
Frontoparietal	RS	grad1	diagnostic_groupcontrol	0.0048787	0.0121007	0.4031766	0.6870740	0.7774983
Language	RS	grad1	diagnostic_groupcontrol	0.0088708	0.0152402	0.5820622	0.5609140	0.6730968
Orbito-Affective	RS	grad1	diagnostic_groupcontrol	-0.0069285	0.0155307	-0.4461156	0.6558002	0.7634689
Posterior-Multimodal	RS	grad1	diagnostic_groupcontrol	-0.0249197	0.0193463	-1.2880865	0.1985996	0.3901503
Somatomotor	RS	grad1	diagnostic_groupcontrol	-0.0123419	0.0134545	-0.9173031	0.3596398	0.5844480
Subcortical	RS	grad1	diagnostic_groupcontrol	0.0182000	0.0114169	1.5941232	0.1118458	0.2492565
Ventral-Multimodal	RS	grad1	diagnostic_groupcontrol	0.0334800	0.0197041	1.6991425	0.0902152	0.2132359
Visual1	RS	grad1	diagnostic_groupcontrol	-0.0594700	0.0214347	-2.7744708	0.0058374	0.0284573
Visual2	RS	grad1	diagnostic_groupcontrol	-0.0242399	0.0124447	-1.9478128	0.0522674	0.1456021
Auditory	EA	grad2	diagnostic_groupcontrol	-0.0132153	0.0096221	-1.3734335	0.1705306	0.3500366
Cingulo-Opercular	EA	grad2	diagnostic_groupcontrol	0.0046755	0.0050972	0.9172640	0.3596603	0.5844480
Default	EA	grad2	diagnostic_groupcontrol	0.0002702	0.0036744	0.0735465	0.9414148	0.9536410
Dorsal-Attention	EA	grad2	diagnostic_groupcontrol	-0.0038127	0.0065339	-0.5835214	0.5599327	0.6730968
Frontoparietal	EA	grad2	diagnostic_groupcontrol	0.0010002	0.0044215	0.2262056	0.8211787	0.8655667
Language	EA	grad2	diagnostic_groupcontrol	-0.0133176	0.0061530	-2.1643975	0.0311357	0.1006633
Orbito-Affective	EA	grad2	diagnostic_groupcontrol	0.0218019	0.0074438	2.9288783	0.0036335	0.0202441
Posterior-Multimodal	EA	grad2	diagnostic_groupcontrol	-0.0085209	0.0097965	-0.8697876	0.3850356	0.6006555
Somatomotor	EA	grad2	diagnostic_groupcontrol	-0.0014679	0.0078331	-0.1873912	0.8514667	0.8855253
Subcortical	EA	grad2	diagnostic_groupcontrol	-0.0019997	0.0061273	-0.3263526	0.7443602	0.8177478
Ventral-Multimodal	EA	grad2	diagnostic_groupcontrol	-0.0066462	0.0093836	-0.7082754	0.4792639	0.6511018
Visual1	EA	grad2	diagnostic_groupcontrol	0.0096343	0.0121732	0.7914346	0.4292471	0.6193960
Visual2	EA	grad2	diagnostic_groupcontrol	0.0058452	0.0087851	0.6653587	0.5062762	0.6630601
Auditory	RS	grad2	diagnostic_groupcontrol	-0.0613518	0.0163841	-3.7445960	0.0002124	0.0033139
Cingulo-Opercular	RS	grad2	diagnostic_groupcontrol	-0.0419363	0.0095306	-4.4001802	0.0000145	0.0003778
Default	RS	grad2	diagnostic_groupcontrol	-0.0074203	0.0065580	-1.1314897	0.2586535	0.4697058
Dorsal-Attention	RS	grad2	diagnostic_groupcontrol	0.0414994	0.0132380	3.1348567	0.0018705	0.0112232
Frontoparietal	RS	grad2	diagnostic_groupcontrol	-0.0179810	0.0074568	-2.4113765	0.0164268	0.0582404
Language	RS	grad2	diagnostic_groupcontrol	0.0092382	0.0111450	0.8289069	0.4077438	0.6116157
Orbito-Affective	RS	grad2	diagnostic_groupcontrol	-0.0110916	0.0136109	-0.8149061	0.4157016	0.6117872
Posterior-Multimodal	RS	grad2	diagnostic_groupcontrol	0.0198206	0.0172853	1.1466741	0.2523298	0.4697058
Somatomotor	RS	grad2	diagnostic_groupcontrol	-0.0381138	0.0142219	-2.6799330	0.0077253	0.0334765
Subcortical	RS	grad2	diagnostic_groupcontrol	-0.0282857	0.0087827	-3.2206173	0.0014038	0.0091245
Ventral-Multimodal	RS	grad2	diagnostic_groupcontrol	0.0073589	0.0182964	0.4022066	0.6877870	0.7774983
Visual1	RS	grad2	diagnostic_groupcontrol	0.0179466	0.0256228	0.7004131	0.4841526	0.6511018
Visual2	RS	grad2	diagnostic_groupcontrol	0.1144097	0.0157738	7.2531338	0.0000000	0.0000000
Auditory	EA	grad3	diagnostic_groupcontrol	-0.0156858	0.0110482	-1.4197603	0.1566019	0.3393040
Cingulo-Opercular	EA	grad3	diagnostic_groupcontrol	0.0044706	0.0049661	0.9002179	0.3686472	0.5868261
Default	EA	grad3	diagnostic_groupcontrol	0.0034915	0.0054026	0.6462660	0.5185470	0.6630601
Dorsal-Attention	EA	grad3	diagnostic_groupcontrol	0.0017452	0.0067718	0.2577188	0.7967813	0.8513553
Frontoparietal	EA	grad3	diagnostic_groupcontrol	0.0031561	0.0061960	0.5093809	0.6108187	0.7218766
Language	EA	grad3	diagnostic_groupcontrol	0.0031840	0.0088005	0.3618029	0.7177260	0.7997519
Orbito-Affective	EA	grad3	diagnostic_groupcontrol	-0.0057439	0.0088543	-0.6487161	0.5169637	0.6630601
Posterior-Multimodal	EA	grad3	diagnostic_groupcontrol	0.0299112	0.0114921	2.6027559	0.0096563	0.0376597
Somatomotor	EA	grad3	diagnostic_groupcontrol	-0.0209442	0.0063079	-3.3203199	0.0009976	0.0077814
Subcortical	EA	grad3	diagnostic_groupcontrol	0.0226621	0.0062437	3.6296057	0.0003279	0.0036180
Ventral-Multimodal	EA	grad3	diagnostic_groupcontrol	-0.0112839	0.0106985	-1.0547187	0.2923096	0.5066699
Visual1	EA	grad3	diagnostic_groupcontrol	-0.0142646	0.0085054	-1.6771183	0.0944466	0.2166716
Visual2	EA	grad3	diagnostic_groupcontrol	-0.0053467	0.0038924	-1.3736174	0.1704736	0.3500366
Auditory	RS	grad3	diagnostic_groupcontrol	0.0121786	0.0156414	0.7786139	0.4367536	0.6193960
Cingulo-Opercular	RS	grad3	diagnostic_groupcontrol	0.0067627	0.0080353	0.8416301	0.4005919	0.6116157
Default	RS	grad3	diagnostic_groupcontrol	0.0235588	0.0071710	3.2852716	0.0011260	0.0079840
Dorsal-Attention	RS	grad3	diagnostic_groupcontrol	-0.0253400	0.0110227	-2.2989032	0.0221218	0.0750218
Frontoparietal	RS	grad3	diagnostic_groupcontrol	0.0051760	0.0085082	0.6083469	0.5433672	0.6730968
Language	RS	grad3	diagnostic_groupcontrol	-0.0239176	0.0120263	-1.9887681	0.0475352	0.1373238
Orbito-Affective	RS	grad3	diagnostic_groupcontrol	0.0402752	0.0152691	2.6376983	0.0087341	0.0358556
Posterior-Multimodal	RS	grad3	diagnostic_groupcontrol	-0.0206704	0.0182793	-1.1308072	0.2589404	0.4697058
Somatomotor	RS	grad3	diagnostic_groupcontrol	-0.0180773	0.0103476	-1.7469985	0.0815486	0.1987746
Subcortical	RS	grad3	diagnostic_groupcontrol	0.0410243	0.0101849	4.0279734	0.0000696	0.0013565
Ventral-Multimodal	RS	grad3	diagnostic_groupcontrol	-0.0345523	0.0179343	-1.9266061	0.0548694	0.1475797
Visual1	RS	grad3	diagnostic_groupcontrol	-0.0571140	0.0167060	-3.4187666	0.0007062	0.0061204
Visual2	RS	grad3	diagnostic_groupcontrol	-0.0299806	0.0083366	-3.5962783	0.0003711	0.0036180

net_centroids_results %>%
  filter(term == "diagnostic_groupcontrol") %>%
  arrange(grad_num, Task) %>%
  knitr::kable()

Network	Task	grad_num	term	estimate	std.error	statistic	p.value	p_FDR
Auditory	EA	grad1	diagnostic_groupcontrol	0.0239680	0.0092808	2.5825409	0.0102288	0.0379928
Cingulo-Opercular	EA	grad1	diagnostic_groupcontrol	0.0146874	0.0068312	2.1500320	0.0322639	0.1006633
Default	EA	grad1	diagnostic_groupcontrol	-0.0376677	0.0078740	-4.7838048	0.0000026	0.0001005
Dorsal-Attention	EA	grad1	diagnostic_groupcontrol	0.0065356	0.0061926	1.0553855	0.2920051	0.5066699
Frontoparietal	EA	grad1	diagnostic_groupcontrol	-0.0083782	0.0065259	-1.2838482	0.2000771	0.3901503
Language	EA	grad1	diagnostic_groupcontrol	0.0145716	0.0079548	1.8317936	0.0678647	0.1764481
Orbito-Affective	EA	grad1	diagnostic_groupcontrol	0.0004807	0.0087882	0.0547014	0.9564087	0.9564087
Posterior-Multimodal	EA	grad1	diagnostic_groupcontrol	-0.0064001	0.0108629	-0.5891675	0.5561436	0.6730968
Somatomotor	EA	grad1	diagnostic_groupcontrol	0.0162528	0.0089713	1.8116381	0.0709322	0.1784746
Subcortical	EA	grad1	diagnostic_groupcontrol	-0.0014148	0.0052628	-0.2688300	0.7882250	0.8513553
Ventral-Multimodal	EA	grad1	diagnostic_groupcontrol	-0.0095459	0.0100210	-0.9525960	0.3414775	0.5790271
Visual1	EA	grad1	diagnostic_groupcontrol	0.0068381	0.0091587	0.7466176	0.4558150	0.6348852
Visual2	EA	grad1	diagnostic_groupcontrol	0.0168989	0.0061751	2.7366396	0.0065361	0.0299890
Auditory	RS	grad1	diagnostic_groupcontrol	0.0336612	0.0161283	2.0870909	0.0376309	0.1128928
Cingulo-Opercular	RS	grad1	diagnostic_groupcontrol	0.0357243	0.0097576	3.6611913	0.0002914	0.0036180
Default	RS	grad1	diagnostic_groupcontrol	-0.0345143	0.0122000	-2.8290313	0.0049485	0.0257323
Dorsal-Attention	RS	grad1	diagnostic_groupcontrol	-0.0016279	0.0107539	-0.1513808	0.8797659	0.9029177
Frontoparietal	RS	grad1	diagnostic_groupcontrol	0.0048787	0.0121007	0.4031766	0.6870740	0.7774983
Language	RS	grad1	diagnostic_groupcontrol	0.0088708	0.0152402	0.5820622	0.5609140	0.6730968
Orbito-Affective	RS	grad1	diagnostic_groupcontrol	-0.0069285	0.0155307	-0.4461156	0.6558002	0.7634689
Posterior-Multimodal	RS	grad1	diagnostic_groupcontrol	-0.0249197	0.0193463	-1.2880865	0.1985996	0.3901503
Somatomotor	RS	grad1	diagnostic_groupcontrol	-0.0123419	0.0134545	-0.9173031	0.3596398	0.5844480
Subcortical	RS	grad1	diagnostic_groupcontrol	0.0182000	0.0114169	1.5941232	0.1118458	0.2492565
Ventral-Multimodal	RS	grad1	diagnostic_groupcontrol	0.0334800	0.0197041	1.6991425	0.0902152	0.2132359
Visual1	RS	grad1	diagnostic_groupcontrol	-0.0594700	0.0214347	-2.7744708	0.0058374	0.0284573
Visual2	RS	grad1	diagnostic_groupcontrol	-0.0242399	0.0124447	-1.9478128	0.0522674	0.1456021
Auditory	EA	grad2	diagnostic_groupcontrol	-0.0132153	0.0096221	-1.3734335	0.1705306	0.3500366
Cingulo-Opercular	EA	grad2	diagnostic_groupcontrol	0.0046755	0.0050972	0.9172640	0.3596603	0.5844480
Default	EA	grad2	diagnostic_groupcontrol	0.0002702	0.0036744	0.0735465	0.9414148	0.9536410
Dorsal-Attention	EA	grad2	diagnostic_groupcontrol	-0.0038127	0.0065339	-0.5835214	0.5599327	0.6730968
Frontoparietal	EA	grad2	diagnostic_groupcontrol	0.0010002	0.0044215	0.2262056	0.8211787	0.8655667
Language	EA	grad2	diagnostic_groupcontrol	-0.0133176	0.0061530	-2.1643975	0.0311357	0.1006633
Orbito-Affective	EA	grad2	diagnostic_groupcontrol	0.0218019	0.0074438	2.9288783	0.0036335	0.0202441
Posterior-Multimodal	EA	grad2	diagnostic_groupcontrol	-0.0085209	0.0097965	-0.8697876	0.3850356	0.6006555
Somatomotor	EA	grad2	diagnostic_groupcontrol	-0.0014679	0.0078331	-0.1873912	0.8514667	0.8855253
Subcortical	EA	grad2	diagnostic_groupcontrol	-0.0019997	0.0061273	-0.3263526	0.7443602	0.8177478
Ventral-Multimodal	EA	grad2	diagnostic_groupcontrol	-0.0066462	0.0093836	-0.7082754	0.4792639	0.6511018
Visual1	EA	grad2	diagnostic_groupcontrol	0.0096343	0.0121732	0.7914346	0.4292471	0.6193960
Visual2	EA	grad2	diagnostic_groupcontrol	0.0058452	0.0087851	0.6653587	0.5062762	0.6630601
Auditory	RS	grad2	diagnostic_groupcontrol	-0.0613518	0.0163841	-3.7445960	0.0002124	0.0033139
Cingulo-Opercular	RS	grad2	diagnostic_groupcontrol	-0.0419363	0.0095306	-4.4001802	0.0000145	0.0003778
Default	RS	grad2	diagnostic_groupcontrol	-0.0074203	0.0065580	-1.1314897	0.2586535	0.4697058
Dorsal-Attention	RS	grad2	diagnostic_groupcontrol	0.0414994	0.0132380	3.1348567	0.0018705	0.0112232
Frontoparietal	RS	grad2	diagnostic_groupcontrol	-0.0179810	0.0074568	-2.4113765	0.0164268	0.0582404
Language	RS	grad2	diagnostic_groupcontrol	0.0092382	0.0111450	0.8289069	0.4077438	0.6116157
Orbito-Affective	RS	grad2	diagnostic_groupcontrol	-0.0110916	0.0136109	-0.8149061	0.4157016	0.6117872
Posterior-Multimodal	RS	grad2	diagnostic_groupcontrol	0.0198206	0.0172853	1.1466741	0.2523298	0.4697058
Somatomotor	RS	grad2	diagnostic_groupcontrol	-0.0381138	0.0142219	-2.6799330	0.0077253	0.0334765
Subcortical	RS	grad2	diagnostic_groupcontrol	-0.0282857	0.0087827	-3.2206173	0.0014038	0.0091245
Ventral-Multimodal	RS	grad2	diagnostic_groupcontrol	0.0073589	0.0182964	0.4022066	0.6877870	0.7774983
Visual1	RS	grad2	diagnostic_groupcontrol	0.0179466	0.0256228	0.7004131	0.4841526	0.6511018
Visual2	RS	grad2	diagnostic_groupcontrol	0.1144097	0.0157738	7.2531338	0.0000000	0.0000000
Auditory	EA	grad3	diagnostic_groupcontrol	-0.0156858	0.0110482	-1.4197603	0.1566019	0.3393040
Cingulo-Opercular	EA	grad3	diagnostic_groupcontrol	0.0044706	0.0049661	0.9002179	0.3686472	0.5868261
Default	EA	grad3	diagnostic_groupcontrol	0.0034915	0.0054026	0.6462660	0.5185470	0.6630601
Dorsal-Attention	EA	grad3	diagnostic_groupcontrol	0.0017452	0.0067718	0.2577188	0.7967813	0.8513553
Frontoparietal	EA	grad3	diagnostic_groupcontrol	0.0031561	0.0061960	0.5093809	0.6108187	0.7218766
Language	EA	grad3	diagnostic_groupcontrol	0.0031840	0.0088005	0.3618029	0.7177260	0.7997519
Orbito-Affective	EA	grad3	diagnostic_groupcontrol	-0.0057439	0.0088543	-0.6487161	0.5169637	0.6630601
Posterior-Multimodal	EA	grad3	diagnostic_groupcontrol	0.0299112	0.0114921	2.6027559	0.0096563	0.0376597
Somatomotor	EA	grad3	diagnostic_groupcontrol	-0.0209442	0.0063079	-3.3203199	0.0009976	0.0077814
Subcortical	EA	grad3	diagnostic_groupcontrol	0.0226621	0.0062437	3.6296057	0.0003279	0.0036180
Ventral-Multimodal	EA	grad3	diagnostic_groupcontrol	-0.0112839	0.0106985	-1.0547187	0.2923096	0.5066699
Visual1	EA	grad3	diagnostic_groupcontrol	-0.0142646	0.0085054	-1.6771183	0.0944466	0.2166716
Visual2	EA	grad3	diagnostic_groupcontrol	-0.0053467	0.0038924	-1.3736174	0.1704736	0.3500366
Auditory	RS	grad3	diagnostic_groupcontrol	0.0121786	0.0156414	0.7786139	0.4367536	0.6193960
Cingulo-Opercular	RS	grad3	diagnostic_groupcontrol	0.0067627	0.0080353	0.8416301	0.4005919	0.6116157
Default	RS	grad3	diagnostic_groupcontrol	0.0235588	0.0071710	3.2852716	0.0011260	0.0079840
Dorsal-Attention	RS	grad3	diagnostic_groupcontrol	-0.0253400	0.0110227	-2.2989032	0.0221218	0.0750218
Frontoparietal	RS	grad3	diagnostic_groupcontrol	0.0051760	0.0085082	0.6083469	0.5433672	0.6730968
Language	RS	grad3	diagnostic_groupcontrol	-0.0239176	0.0120263	-1.9887681	0.0475352	0.1373238
Orbito-Affective	RS	grad3	diagnostic_groupcontrol	0.0402752	0.0152691	2.6376983	0.0087341	0.0358556
Posterior-Multimodal	RS	grad3	diagnostic_groupcontrol	-0.0206704	0.0182793	-1.1308072	0.2589404	0.4697058
Somatomotor	RS	grad3	diagnostic_groupcontrol	-0.0180773	0.0103476	-1.7469985	0.0815486	0.1987746
Subcortical	RS	grad3	diagnostic_groupcontrol	0.0410243	0.0101849	4.0279734	0.0000696	0.0013565
Ventral-Multimodal	RS	grad3	diagnostic_groupcontrol	-0.0345523	0.0179343	-1.9266061	0.0548694	0.1475797
Visual1	RS	grad3	diagnostic_groupcontrol	-0.0571140	0.0167060	-3.4187666	0.0007062	0.0061204
Visual2	RS	grad3	diagnostic_groupcontrol	-0.0299806	0.0083366	-3.5962783	0.0003711	0.0036180

all_roi_results <- spins_grads %>%
  inner_join(lol_spins_behav, by = c("Subject" = "subject")) %>%
  mutate( fd_mean = if_else(Task=="EA", fd_mean_emp, `fd_mean.rest_bold`)) %>%
  pivot_longer(grad1:grad4, names_to = "grad_num", values_to = "grad_value") %>%
    ungroup() %>%
  group_by(Network, Task, grad_num, ROI) %>%
  do(tidy(lm(grad_value ~ diagnostic_group + demo_age_study_entry + demo_sex + fd_mean + scanner, data = .))) %>%
  ungroup() %>%
  group_by(term) %>%
  mutate(p_FDR = p.adjust(p.value, method = "fdr"))
  
all_roi_results %>% write_csv('ROIwise_SPINS_SSDvsHC_result_wGSR.csv')

all_roi_results %>%
  filter(term == "diagnostic_groupcontrol", p_FDR < 0.05)

all_roi_results %>%
  filter(term == "diagnostic_groupcontrol", p_FDR < 0.05) %>%
  count(Task, grad_num) %>%
  arrange(Task, grad_num)

all_roi_results %>%
  filter(term == "diagnostic_groupcontrol", p_FDR < 0.05) %>%
  count(Task, grad_num, Network) %>%
  pivot_wider(names_from = grad_num, values_from = n)